Recent advances in memristors based on two-dimensional ferroelectric materials

Abstract

In this big data era, the explosive growth of information puts ultra-high demands on the data storage/computing, such as high computing power, low energy consumption, and excellent stability. However, facing this challenge, the traditional von Neumann architecture-based computing system is out of its depth owing to the separated memory and data processing unit architecture. One of the most effective ways to solve this challenge is building brain inspired computing system with in-memory computing and parallel processing ability based on neuromorphic devices. Therefore, there is a research trend toward the memristors, that can be applied to build neuromorphic computing systems due to their large switching ratio, high storage density, low power consumption, and high stability. Two-dimensional (2D) ferroelectric materials, as novel types of functional materials, show great potential in the preparations of memristors because of the atomic scale thickness, high carrier mobility, mechanical flexibility, and thermal stability. 2D ferroelectric materials can realize resistive switching (RS) because of the presence of natural dipoles whose direction can be flipped with the change of the applied electric field thus producing different polarizations, therefore, making them powerful candidates for future data storage and computing. In this review article, we introduce the physical mechanisms, characterizations, and synthetic methods of 2D ferroelectric materials, and then summarize the applications of 2D ferroelectric materials in memristors for memory and synaptic devices. At last, we deliberate the advantages and future challenges of 2D ferroelectric materials in the application of memristors devices.

Graphical abstract

Keywords

two-dimensional ferroelectric materials / synthesis strategies / memristors / artificial synapses

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Declarations

The authors declare that they have no competing interests and there are no conflicts.

Acknowledgements

We acknowledge grants from the National Natural Science Foundation of China (Grant No. 61974093), the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2023A1515012479), the Science and Technology Innovation Commission of Shenzhen (Grant Nos. RCYX20200714114524157 and JCYJ20220818100206013), and the NTUT-SZU Joint Research Program (Grant No. NTUT-SZU-112-02).

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